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New Algorithms for Performance Trace Analysis Based on Compressed Complete Call Graphs

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Part of the book series:Lecture Notes in Computer Science ((LNTCS,volume 3515))

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Abstract

This paper addresses performance and scalability issues of state-of-the-art trace analysis. The Complete Call Graph (CCG) data structure is proposed as an alternative to the common linear storage schemes. By transparent in-memory compression CCGs are capable of exploiting redundancy as frequently found in traces and thus reduce the memory requirements notably. Evaluation algorithms can be designed to take advantage of CCGs, too, such that the computational effort is reduced in the same order of magnitude as the memory requirements.

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Author information

Authors and Affiliations

  1. Center for High Performance Computing, Dresden University of Technology, Germany

    Andreas Knüpfer & Wolfgang E. Nagel

Authors
  1. Andreas Knüpfer

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  2. Wolfgang E. Nagel

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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, Emory University, Atlanta, Georgia, USA

    Vaidy S. Sunderam

  2. Department of Mathematics and Computer Science, University of Amsterdam, Kruislaan 403, 1098, Amsterdam, SJ, The Netherlands

    Geert Dick van Albada

  3. Faculty of Sciences, Section of Computational Science, University of Amsterdam, Kruislaan 403, 1098, Amsterdam, SJ, The Netherlands

    Peter M. A. Sloot

  4. Computer Science Department, University of Tennessee, 37996-3450, TN, Knoxville, USA

    Jack J. Dongarra

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© 2005 Springer-Verlag Berlin Heidelberg

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Knüpfer, A., Nagel, W.E. (2005). New Algorithms for Performance Trace Analysis Based on Compressed Complete Call Graphs. In: Sunderam, V.S., van Albada, G.D., Sloot, P.M.A., Dongarra, J.J. (eds) Computational Science – ICCS 2005. ICCS 2005. Lecture Notes in Computer Science, vol 3515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428848_15

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